Results 171 to 180 of about 7,459,988 (350)
Principles for Designing Ideal Protein Structures
Seibutsu Butsuri, 2013 Nobuyasu Koga, Rie Tatsumi-Koga
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Advanced Biology, EarlyView.Infrared (IR) light evokes distinct calcium and water transport responses in astrocytes, depending on stimulation duration and protocol. This study uses widefield imaging and pharmacology to reveal differential engagement of astroglial signaling pathways.
Wilson R. Adams +7 more
wiley +1 more source
The illustration of random-walk ideal chain model and the relationship with real protein chain.
, 2010 Jian Zhang, Yang Zhang
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Effects of a near ideal amino acid balance diet on lysine mammary utilization, whole body protein turnover and muscle protein breakdown on lactating sows [PDF]
, 2023 Sai Zhang +6 more
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Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Advanced Engineering Materials, EarlyView.Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani +2 more
wiley +1 more source
Current knowledge about ideal protein for growing pigs
, 2014 absent
van Milgen, Jaap +3 more
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Advanced Engineering Materials, EarlyView.Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source